AI Explored Podcast
Successfully Deploying AI for Traditional Businesses
Host: Michael Stelzner
Guest: Carl Yeh, Co-founder of Zero to 60 AI
Date: October 7, 2025

Overview

This episode of AI Explored dives into the how-tos and challenges of adopting AI in traditional businesses. Host Michael Stelzner interviews AI strategist Carl Yeh, who specializes in helping mid-sized, longstanding businesses deploy AI solutions. Together, they address the misconceptions around AI, outline actionable steps to implement it, and explore real-world examples and tools. The focus is on practical strategies: from identifying the right “eye roll” tasks for AI, to gaining buy-in, piloting, and scaling AI initiatives, and future-proofing organizations for the fast-evolving AI economy.

Key Discussion Points & Insights

Carl Yeh’s Journey Into AI (03:29–05:20)

• Started exploring AI in 2014, inspired by industry leaders like Paul Roetzer.
• Interest was solidified by witnessing Google's 2018 AI restaurant reservation demo.
• Shifted from marketing/content creation to AI consulting as interest and need spiked after 2022.
• Leveraged his coding background and industry connections to start Zero to 60 AI in 2023.

“It was… Sundar [Pichai] do this restaurant reservation through AI and I thought this is the coolest thing I’ve ever seen. ...That’s where I really dug deep because I thought this is coming now.”
— Carl Yeh (03:45)

Common Misconceptions about AI Adoption (05:20–07:47)

1. Ease of Implementation:
   Many assume AI is simply “bolted on” for instant efficiency, not realizing true gains come from rebuilding processes with an AI-centric mindset.
2. Short-term Adoption:
   Sustained, not one-off, adoption is crucial—3, 6, 12 months and beyond.
3. Change Management Underestimated:
   Companies underestimate the behavioral and cultural shifts required, especially in organizations with entrenched processes.

"Bolting on AI to your process, your workflows, or even a product isn't good enough. ...You have to rebuild your processes and systems from ground up, being AI centric."
— Carl Yeh (06:19)

The Real Threat: Native AI Companies (07:47–09:32)

• The main competitive threat comes not from existing rivals but new, “AI native” startups unburdened by legacy systems, able to move quickly and outpace established organizations.

"Your competition will use AI and maybe they'll get a little bit ahead. ...But the danger ...is not really your competition using AI. It's native AI companies ...All their processes are already AI centric."
— Carl Yeh (07:56)

Why Deploy AI Now? What’s the Upside? (10:43–13:49)

• Immediate Gains: Even “bolted-on” solutions yield 10–40% productivity/efficiency improvements.
• Mindset and Upskilling: Training teams in AI (even basic prompting) can multiply performance gains.
• Preparation for the Future: Organizations must evolve to stay competitive as AI disrupts industries.

"We're not saying 95%, full autonomous workflow... Our big thing has always been 10 to 40% to start and then build on from there."
— Carl Yeh (11:11)

Where to Begin: The Discovery Phase (13:49–19:37)

1. Audit Existing Processes:
   Identify repetitive, data-driven, predictive, and “eye roll” tasks within each department.

2. Engage Employees Directly:
   Gather insights from frontline staff—often through sessions that double as complaint forums—to map inefficiencies and potential AI opportunities.

3. Prioritize Change Management and Data Readiness:
   Assess team readiness and clean up data, as dirty data can derail implementation.

"If your employees ...roll their eyes at [tasks]... look at those things."
— Carl Yeh (14:37)

From Discovery to AI Strategy (20:29–26:17)

• Summarize Key Findings:
  Document departmental discoveries and link each “eye roll” task to potential AI (and non-AI) solutions.
• Identify Communication Fixes:
  Some workflow inefficiencies stem from poor inter-departmental communication, not lack of AI—solve these cheaply and immediately.
• Create a Roadmap:
  Develop a multi-phase plan (6–18+ months) with priorities, pilot recommendations, “AI-centric rebuild” candidates, and an overall AI vision for the company.

"Some of these things need to be fixed because people are actually not putting quality together in the first place...that also might mean that could be optimized down the road with AI."
— Michael Stelzner (23:05)

Real-World Example: AI in an Accounting Firm (26:20–29:49)

• Automated manual data entry using on-premise N8N integration with Mistral PDF OCR and QuickBooks.
• Introduced an AI voice receptionist using Bland AI to handle repetitive calls and bookings.

"We used Mistral's PDF reader... they had the best one that could recognize a PDF in different formats... 95–97% reliable."
— Carl Yeh (28:09)

Tips for Successful AI Pilots (30:11–36:04)

• Dedicated Subject Matter Experts:
  Assign clear ownership of pilots—these cannot be side projects.
• AI Champions:
  Cultivate a group within the company to drive enthusiasm, accountability, and ongoing use.
• Behavioral Change:
  Adoption rates drop unless regular reminders, support, and accountability checkpoints are built in.

"You need a group to keep people accountable, to keep using whatever solution you had. ...It's those kind of things, right? ...There's a lot of human behavior you have to change."
— Carl Yeh (34:24)

Bottom-Up or Top-Down? Gaining Buy-In (36:04–38:02)

• Beware simply mandating AI from above or letting adoption be ad hoc—balance leadership support with ground-level buy-in and tailored solutions.

"Worse is if actually leaders get excited about a demo they've seen before, buy a tool, and then enforce that tool into the company."
— Carl Yeh (36:49)

Ongoing Training & Staying Agile (39:42–42:01)

• Regular, iterative AI training is necessary, as tools and best practices evolve rapidly.
• Assign AI committees not just to review pilots but also to update trainings, keep staff aligned, and propagate changes as AI capabilities advance.

"Even the training we did for a company three months ago, we kind of need to update it...That's a completely different way for businesses to operate."
— Carl Yeh (39:50)

Scaling and Continuous Improvement (42:12–44:11)

• Pilots must be flexible—what works now will quickly be superseded; iterate and take advantage of new AI features.
• Example: Evolving invoice consolidation—from manual uploads, to custom GPTs, to agent-based automations running on a schedule, eliminating user intervention.

"That’s the next part... Now there's no dragging and dropping... You have a scheduled agent to do [the task] every Friday."
— Carl Yeh (43:14)

Memorable Quotes

• “The real danger is not your competition embracing AI; it's native AI companies that don't have change management, don't have to bolt on processes. All their processes are already AI centric.” (Carl Yeh, 07:56)
• "Discovery isn't even about talking a lot about AI; it's about understanding the business’s current processes, especially those 'eye roll' tasks frontline staff dread." (Carl Yeh, 14:37)
• "You need a group to keep people accountable, to keep using whatever solution you had." (Carl Yeh, 34:24)
• "They're funding it. There will be companies in your industry that are going to be native that will maybe have significantly less people that can do significantly more." (Carl Yeh, 41:25)
• "If you employ this, those eye roll tasks will dissipate. ...With that newfound time, you can work on higher order tasks like analyzing things or being creative or working on strategy." (Michael Stelzner, 38:11)
• "All you have to do is go to Y Combinator, go for the request for startups, their summer 2025. They literally say it on the thing. Instead of working with the dinosaurs, you can make them extinct." (Carl Yeh, 41:00)

Timestamps for Key Segments

• 03:29 — Carl Yeh’s AI Journey
• 05:20 — Biggest Misconceptions About AI Adoption
• 07:47 — Real Risks: Traditional vs. Native AI Competitors
• 10:43 — The Value Proposition: Why Deploy AI Now
• 13:49 — Discovery Phase: Where to Start
• 19:37 — Departmental Audits and Practical Considerations
• 26:20 — Case Study: AI in Accounting
• 30:11 — Structuring Pilots, Role of Champions
• 33:13 — Subject Matter Experts vs. AI Champions
• 36:04 — Buy-In: Top-Down or Bottom-Up?
• 39:42 — Iterative Training and Evolution
• 42:12 — Scaling Pilots, Embracing Change

Additional Resources & Contact

• Carl Yeh:

  • Website: Zero to 60 AI
  • Show: AI Accelerator for Business (YouTube, podcasts)
  • TikTok: @carl.yeh

• Full episode notes: socialmediaexaminer.com/aipod